diff --git a/api/apps/langfuse_app.py b/api/apps/langfuse_app.py new file mode 100644 index 000000000..7a7355036 --- /dev/null +++ b/api/apps/langfuse_app.py @@ -0,0 +1,58 @@ +# +# Copyright 2025 The InfiniFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + + +from flask import request +from flask_login import current_user, login_required +from langfuse import Langfuse + +from api.db.db_models import DB +from api.db.services.langfuse_service import TenantLangfuseService +from api.utils.api_utils import get_error_data_result, get_json_result, server_error_response, validate_request + + +@manager.route("/set_api_key", methods=["POST"]) # noqa: F821 +@login_required +@validate_request("secret_key", "public_key", "host") +def set_api_key(): + req = request.get_json() + secret_key = req.get("secret_key", "") + public_key = req.get("public_key", "") + host = req.get("host", "") + if not all([secret_key, public_key, host]): + return get_error_data_result(message="Missing required fields") + + langfuse_keys = dict( + tenant_id=current_user.id, + secret_key=secret_key, + public_key=public_key, + host=host, + ) + + langfuse = Langfuse(public_key=langfuse_keys["public_key"], secret_key=langfuse_keys["secret_key"], host=langfuse_keys["host"]) + if not langfuse.auth_check(): + return get_error_data_result(message="Invalid Langfuse keys") + + langfuse_entry = TenantLangfuseService.filter_by_tenant(tenant_id=current_user.id) + with DB.atomic(): + try: + if not langfuse_entry: + TenantLangfuseService.save(**langfuse_keys) + else: + TenantLangfuseService.update_by_tenant(tenant_id=current_user.id, langfuse_keys=langfuse_keys) + return get_json_result(data=True) + except Exception as e: + server_error_response(e) diff --git a/api/db/db_models.py b/api/db/db_models.py index 9f7e4ac8b..7ba6164a7 100644 --- a/api/db/db_models.py +++ b/api/db/db_models.py @@ -13,27 +13,23 @@ # See the License for the specific language governing permissions and # limitations under the License. # -import logging import inspect +import logging +import operator import os import sys import typing -import operator from enum import Enum from functools import wraps -from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer + from flask_login import UserMixin +from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer +from peewee import BigIntegerField, BooleanField, CharField, CompositeKey, DateTimeField, Field, FloatField, IntegerField, Metadata, Model, TextField from playhouse.migrate import MySQLMigrator, PostgresqlMigrator, migrate -from peewee import ( - BigIntegerField, BooleanField, CharField, - CompositeKey, IntegerField, TextField, FloatField, DateTimeField, - Field, Model, Metadata -) from playhouse.pool import PooledMySQLDatabase, PooledPostgresqlDatabase -from api.db import SerializedType, ParserType -from api import settings -from api import utils +from api import settings, utils +from api.db import ParserType, SerializedType def singleton(cls, *args, **kw): @@ -49,18 +45,12 @@ def singleton(cls, *args, **kw): CONTINUOUS_FIELD_TYPE = {IntegerField, FloatField, DateTimeField} -AUTO_DATE_TIMESTAMP_FIELD_PREFIX = { - "create", - "start", - "end", - "update", - "read_access", - "write_access"} +AUTO_DATE_TIMESTAMP_FIELD_PREFIX = {"create", "start", "end", "update", "read_access", "write_access"} class TextFieldType(Enum): - MYSQL = 'LONGTEXT' - POSTGRES = 'TEXT' + MYSQL = "LONGTEXT" + POSTGRES = "TEXT" class LongTextField(TextField): @@ -83,8 +73,7 @@ class JSONField(LongTextField): def python_value(self, value): if not value: return self.default_value - return utils.json_loads( - value, object_hook=self._object_hook, object_pairs_hook=self._object_pairs_hook) + return utils.json_loads(value, object_hook=self._object_hook, object_pairs_hook=self._object_pairs_hook) class ListField(JSONField): @@ -92,8 +81,7 @@ class ListField(JSONField): class SerializedField(LongTextField): - def __init__(self, serialized_type=SerializedType.PICKLE, - object_hook=None, object_pairs_hook=None, **kwargs): + def __init__(self, serialized_type=SerializedType.PICKLE, object_hook=None, object_pairs_hook=None, **kwargs): self._serialized_type = serialized_type self._object_hook = object_hook self._object_pairs_hook = object_pairs_hook @@ -107,8 +95,7 @@ class SerializedField(LongTextField): return None return utils.json_dumps(value, with_type=True) else: - raise ValueError( - f"the serialized type {self._serialized_type} is not supported") + raise ValueError(f"the serialized type {self._serialized_type} is not supported") def python_value(self, value): if self._serialized_type == SerializedType.PICKLE: @@ -116,11 +103,9 @@ class SerializedField(LongTextField): elif self._serialized_type == SerializedType.JSON: if value is None: return {} - return utils.json_loads( - value, object_hook=self._object_hook, object_pairs_hook=self._object_pairs_hook) + return utils.json_loads(value, object_hook=self._object_hook, object_pairs_hook=self._object_pairs_hook) else: - raise ValueError( - f"the serialized type {self._serialized_type} is not supported") + raise ValueError(f"the serialized type {self._serialized_type} is not supported") def is_continuous_field(cls: typing.Type) -> bool: @@ -145,7 +130,7 @@ def auto_date_timestamp_db_field(): def remove_field_name_prefix(field_name): - return field_name[2:] if field_name.startswith('f_') else field_name + return field_name[2:] if field_name.startswith("f_") else field_name class BaseModel(Model): @@ -159,20 +144,19 @@ class BaseModel(Model): return self.to_dict() def to_dict(self): - return self.__dict__['__data__'] + return self.__dict__["__data__"] def to_human_model_dict(self, only_primary_with: list = None): - model_dict = self.__dict__['__data__'] + model_dict = self.__dict__["__data__"] if not only_primary_with: - return {remove_field_name_prefix( - k): v for k, v in model_dict.items()} + return {remove_field_name_prefix(k): v for k, v in model_dict.items()} human_model_dict = {} for k in self._meta.primary_key.field_names: human_model_dict[remove_field_name_prefix(k)] = model_dict[k] for k in only_primary_with: - human_model_dict[k] = model_dict[f'f_{k}'] + human_model_dict[k] = model_dict[f"f_{k}"] return human_model_dict @property @@ -181,8 +165,7 @@ class BaseModel(Model): @classmethod def get_primary_keys_name(cls): - return cls._meta.primary_key.field_names if isinstance(cls._meta.primary_key, CompositeKey) else [ - cls._meta.primary_key.name] + return cls._meta.primary_key.field_names if isinstance(cls._meta.primary_key, CompositeKey) else [cls._meta.primary_key.name] @classmethod def getter_by(cls, attr): @@ -192,7 +175,7 @@ class BaseModel(Model): def query(cls, reverse=None, order_by=None, **kwargs): filters = [] for f_n, f_v in kwargs.items(): - attr_name = '%s' % f_n + attr_name = "%s" % f_n if not hasattr(cls, attr_name) or f_v is None: continue if type(f_v) in {list, set}: @@ -200,22 +183,17 @@ class BaseModel(Model): if is_continuous_field(type(getattr(cls, attr_name))): if len(f_v) == 2: for i, v in enumerate(f_v): - if isinstance( - v, str) and f_n in auto_date_timestamp_field(): + if isinstance(v, str) and f_n in auto_date_timestamp_field(): # time type: %Y-%m-%d %H:%M:%S f_v[i] = utils.date_string_to_timestamp(v) lt_value = f_v[0] gt_value = f_v[1] if lt_value is not None and gt_value is not None: - filters.append( - cls.getter_by(attr_name).between( - lt_value, gt_value)) + filters.append(cls.getter_by(attr_name).between(lt_value, gt_value)) elif lt_value is not None: - filters.append( - operator.attrgetter(attr_name)(cls) >= lt_value) + filters.append(operator.attrgetter(attr_name)(cls) >= lt_value) elif gt_value is not None: - filters.append( - operator.attrgetter(attr_name)(cls) <= gt_value) + filters.append(operator.attrgetter(attr_name)(cls) <= gt_value) else: filters.append(operator.attrgetter(attr_name)(cls) << f_v) else: @@ -226,11 +204,9 @@ class BaseModel(Model): if not order_by or not hasattr(cls, f"{order_by}"): order_by = "create_time" if reverse is True: - query_records = query_records.order_by( - cls.getter_by(f"{order_by}").desc()) + query_records = query_records.order_by(cls.getter_by(f"{order_by}").desc()) elif reverse is False: - query_records = query_records.order_by( - cls.getter_by(f"{order_by}").asc()) + query_records = query_records.order_by(cls.getter_by(f"{order_by}").asc()) return [query_record for query_record in query_records] else: return [] @@ -238,8 +214,7 @@ class BaseModel(Model): @classmethod def insert(cls, __data=None, **insert): if isinstance(__data, dict) and __data: - __data[cls._meta.combined["create_time"] - ] = utils.current_timestamp() + __data[cls._meta.combined["create_time"]] = utils.current_timestamp() if insert: insert["create_time"] = utils.current_timestamp() @@ -252,24 +227,18 @@ class BaseModel(Model): if not normalized: return {} - normalized[cls._meta.combined["update_time"] - ] = utils.current_timestamp() + normalized[cls._meta.combined["update_time"]] = utils.current_timestamp() for f_n in AUTO_DATE_TIMESTAMP_FIELD_PREFIX: - if {f"{f_n}_time", f"{f_n}_date"}.issubset(cls._meta.combined.keys()) and \ - cls._meta.combined[f"{f_n}_time"] in normalized and \ - normalized[cls._meta.combined[f"{f_n}_time"]] is not None: - normalized[cls._meta.combined[f"{f_n}_date"]] = utils.timestamp_to_date( - normalized[cls._meta.combined[f"{f_n}_time"]]) + if {f"{f_n}_time", f"{f_n}_date"}.issubset(cls._meta.combined.keys()) and cls._meta.combined[f"{f_n}_time"] in normalized and normalized[cls._meta.combined[f"{f_n}_time"]] is not None: + normalized[cls._meta.combined[f"{f_n}_date"]] = utils.timestamp_to_date(normalized[cls._meta.combined[f"{f_n}_time"]]) return normalized class JsonSerializedField(SerializedField): - def __init__(self, object_hook=utils.from_dict_hook, - object_pairs_hook=None, **kwargs): - super(JsonSerializedField, self).__init__(serialized_type=SerializedType.JSON, object_hook=object_hook, - object_pairs_hook=object_pairs_hook, **kwargs) + def __init__(self, object_hook=utils.from_dict_hook, object_pairs_hook=None, **kwargs): + super(JsonSerializedField, self).__init__(serialized_type=SerializedType.JSON, object_hook=object_hook, object_pairs_hook=object_pairs_hook, **kwargs) class PooledDatabase(Enum): @@ -288,7 +257,7 @@ class BaseDataBase: database_config = settings.DATABASE.copy() db_name = database_config.pop("name") self.database_connection = PooledDatabase[settings.DATABASE_TYPE.upper()].value(db_name, **database_config) - logging.info('init database on cluster mode successfully') + logging.info("init database on cluster mode successfully") class PostgresDatabaseLock: @@ -301,22 +270,21 @@ class PostgresDatabaseLock: cursor = self.db.execute_sql("SELECT pg_try_advisory_lock(%s)", self.timeout) ret = cursor.fetchone() if ret[0] == 0: - raise Exception(f'acquire postgres lock {self.lock_name} timeout') + raise Exception(f"acquire postgres lock {self.lock_name} timeout") elif ret[0] == 1: return True else: - raise Exception(f'failed to acquire lock {self.lock_name}') + raise Exception(f"failed to acquire lock {self.lock_name}") def unlock(self): cursor = self.db.execute_sql("SELECT pg_advisory_unlock(%s)", self.timeout) ret = cursor.fetchone() if ret[0] == 0: - raise Exception( - f'postgres lock {self.lock_name} was not established by this thread') + raise Exception(f"postgres lock {self.lock_name} was not established by this thread") elif ret[0] == 1: return True else: - raise Exception(f'postgres lock {self.lock_name} does not exist') + raise Exception(f"postgres lock {self.lock_name} does not exist") def __enter__(self): if isinstance(self.db, PostgresDatabaseLock): @@ -344,27 +312,24 @@ class MysqlDatabaseLock: def lock(self): # SQL parameters only support %s format placeholders - cursor = self.db.execute_sql( - "SELECT GET_LOCK(%s, %s)", (self.lock_name, self.timeout)) + cursor = self.db.execute_sql("SELECT GET_LOCK(%s, %s)", (self.lock_name, self.timeout)) ret = cursor.fetchone() if ret[0] == 0: - raise Exception(f'acquire mysql lock {self.lock_name} timeout') + raise Exception(f"acquire mysql lock {self.lock_name} timeout") elif ret[0] == 1: return True else: - raise Exception(f'failed to acquire lock {self.lock_name}') + raise Exception(f"failed to acquire lock {self.lock_name}") def unlock(self): - cursor = self.db.execute_sql( - "SELECT RELEASE_LOCK(%s)", (self.lock_name,)) + cursor = self.db.execute_sql("SELECT RELEASE_LOCK(%s)", (self.lock_name,)) ret = cursor.fetchone() if ret[0] == 0: - raise Exception( - f'mysql lock {self.lock_name} was not established by this thread') + raise Exception(f"mysql lock {self.lock_name} was not established by this thread") elif ret[0] == 1: return True else: - raise Exception(f'mysql lock {self.lock_name} does not exist') + raise Exception(f"mysql lock {self.lock_name} does not exist") def __enter__(self): if isinstance(self.db, PooledMySQLDatabase): @@ -429,7 +394,7 @@ def init_database_tables(alter_fields=[]): def fill_db_model_object(model_object, human_model_dict): for k, v in human_model_dict.items(): - attr_name = '%s' % k + attr_name = "%s" % k if hasattr(model_object.__class__, attr_name): setattr(model_object, attr_name, v) return model_object @@ -440,41 +405,17 @@ class User(DataBaseModel, UserMixin): access_token = CharField(max_length=255, null=True, index=True) nickname = CharField(max_length=100, null=False, help_text="nicky name", index=True) password = CharField(max_length=255, null=True, help_text="password", index=True) - email = CharField( - max_length=255, - null=False, - help_text="email", - index=True) + email = CharField(max_length=255, null=False, help_text="email", index=True) avatar = TextField(null=True, help_text="avatar base64 string") - language = CharField( - max_length=32, - null=True, - help_text="English|Chinese", - default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", - index=True) - color_schema = CharField( - max_length=32, - null=True, - help_text="Bright|Dark", - default="Bright", - index=True) - timezone = CharField( - max_length=64, - null=True, - help_text="Timezone", - default="UTC+8\tAsia/Shanghai", - index=True) + language = CharField(max_length=32, null=True, help_text="English|Chinese", default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", index=True) + color_schema = CharField(max_length=32, null=True, help_text="Bright|Dark", default="Bright", index=True) + timezone = CharField(max_length=64, null=True, help_text="Timezone", default="UTC+8\tAsia/Shanghai", index=True) last_login_time = DateTimeField(null=True, index=True) is_authenticated = CharField(max_length=1, null=False, default="1", index=True) is_active = CharField(max_length=1, null=False, default="1", index=True) is_anonymous = CharField(max_length=1, null=False, default="0", index=True) login_channel = CharField(null=True, help_text="from which user login", index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) is_superuser = BooleanField(null=True, help_text="is root", default=False, index=True) def __str__(self): @@ -493,43 +434,14 @@ class Tenant(DataBaseModel): name = CharField(max_length=100, null=True, help_text="Tenant name", index=True) public_key = CharField(max_length=255, null=True, index=True) llm_id = CharField(max_length=128, null=False, help_text="default llm ID", index=True) - embd_id = CharField( - max_length=128, - null=False, - help_text="default embedding model ID", - index=True) - asr_id = CharField( - max_length=128, - null=False, - help_text="default ASR model ID", - index=True) - img2txt_id = CharField( - max_length=128, - null=False, - help_text="default image to text model ID", - index=True) - rerank_id = CharField( - max_length=128, - null=False, - help_text="default rerank model ID", - index=True) - tts_id = CharField( - max_length=256, - null=True, - help_text="default tts model ID", - index=True) - parser_ids = CharField( - max_length=256, - null=False, - help_text="document processors", - index=True) + embd_id = CharField(max_length=128, null=False, help_text="default embedding model ID", index=True) + asr_id = CharField(max_length=128, null=False, help_text="default ASR model ID", index=True) + img2txt_id = CharField(max_length=128, null=False, help_text="default image to text model ID", index=True) + rerank_id = CharField(max_length=128, null=False, help_text="default rerank model ID", index=True) + tts_id = CharField(max_length=256, null=True, help_text="default tts model ID", index=True) + parser_ids = CharField(max_length=256, null=False, help_text="document processors", index=True) credit = IntegerField(default=512, index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) class Meta: db_table = "tenant" @@ -541,12 +453,7 @@ class UserTenant(DataBaseModel): tenant_id = CharField(max_length=32, null=False, index=True) role = CharField(max_length=32, null=False, help_text="UserTenantRole", index=True) invited_by = CharField(max_length=32, null=False, index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) class Meta: db_table = "user_tenant" @@ -558,35 +465,17 @@ class InvitationCode(DataBaseModel): visit_time = DateTimeField(null=True, index=True) user_id = CharField(max_length=32, null=True, index=True) tenant_id = CharField(max_length=32, null=True, index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) class Meta: db_table = "invitation_code" class LLMFactories(DataBaseModel): - name = CharField( - max_length=128, - null=False, - help_text="LLM factory name", - primary_key=True) + name = CharField(max_length=128, null=False, help_text="LLM factory name", primary_key=True) logo = TextField(null=True, help_text="llm logo base64") - tags = CharField( - max_length=255, - null=False, - help_text="LLM, Text Embedding, Image2Text, ASR", - index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + tags = CharField(max_length=255, null=False, help_text="LLM, Text Embedding, Image2Text, ASR", index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) def __str__(self): return self.name @@ -597,57 +486,27 @@ class LLMFactories(DataBaseModel): class LLM(DataBaseModel): # LLMs dictionary - llm_name = CharField( - max_length=128, - null=False, - help_text="LLM name", - index=True) - model_type = CharField( - max_length=128, - null=False, - help_text="LLM, Text Embedding, Image2Text, ASR", - index=True) + llm_name = CharField(max_length=128, null=False, help_text="LLM name", index=True) + model_type = CharField(max_length=128, null=False, help_text="LLM, Text Embedding, Image2Text, ASR", index=True) fid = CharField(max_length=128, null=False, help_text="LLM factory id", index=True) max_tokens = IntegerField(default=0) - tags = CharField( - max_length=255, - null=False, - help_text="LLM, Text Embedding, Image2Text, Chat, 32k...", - index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + tags = CharField(max_length=255, null=False, help_text="LLM, Text Embedding, Image2Text, Chat, 32k...", index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) def __str__(self): return self.llm_name class Meta: - primary_key = CompositeKey('fid', 'llm_name') + primary_key = CompositeKey("fid", "llm_name") db_table = "llm" class TenantLLM(DataBaseModel): tenant_id = CharField(max_length=32, null=False, index=True) - llm_factory = CharField( - max_length=128, - null=False, - help_text="LLM factory name", - index=True) - model_type = CharField( - max_length=128, - null=True, - help_text="LLM, Text Embedding, Image2Text, ASR", - index=True) - llm_name = CharField( - max_length=128, - null=True, - help_text="LLM name", - default="", - index=True) + llm_factory = CharField(max_length=128, null=False, help_text="LLM factory name", index=True) + model_type = CharField(max_length=128, null=True, help_text="LLM, Text Embedding, Image2Text, ASR", index=True) + llm_name = CharField(max_length=128, null=True, help_text="LLM name", default="", index=True) api_key = CharField(max_length=2048, null=True, help_text="API KEY", index=True) api_base = CharField(max_length=255, null=True, help_text="API Base") max_tokens = IntegerField(default=8192, index=True) @@ -658,36 +517,33 @@ class TenantLLM(DataBaseModel): class Meta: db_table = "tenant_llm" - primary_key = CompositeKey('tenant_id', 'llm_factory', 'llm_name') + primary_key = CompositeKey("tenant_id", "llm_factory", "llm_name") + + +class TenantLangfuse(DataBaseModel): + tenant_id = CharField(max_length=32, null=False, primary_key=True) + secret_key = CharField(max_length=2048, null=False, help_text="SECRET KEY", index=True) + public_key = CharField(max_length=2048, null=False, help_text="PUBLIC KEY", index=True) + host = CharField(max_length=128, null=False, help_text="host", index=True) + # max_tokens = IntegerField(default=8192, index=True) + # used_tokens = IntegerField(default=0, index=True) + + def __str__(self): + return "Langfuse host" + self.host + + class Meta: + db_table = "tenant_langfuse" class Knowledgebase(DataBaseModel): id = CharField(max_length=32, primary_key=True) avatar = TextField(null=True, help_text="avatar base64 string") tenant_id = CharField(max_length=32, null=False, index=True) - name = CharField( - max_length=128, - null=False, - help_text="KB name", - index=True) - language = CharField( - max_length=32, - null=True, - default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", - help_text="English|Chinese", - index=True) + name = CharField(max_length=128, null=False, help_text="KB name", index=True) + language = CharField(max_length=32, null=True, default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", help_text="English|Chinese", index=True) description = TextField(null=True, help_text="KB description") - embd_id = CharField( - max_length=128, - null=False, - help_text="default embedding model ID", - index=True) - permission = CharField( - max_length=16, - null=False, - help_text="me|team", - default="me", - index=True) + embd_id = CharField(max_length=128, null=False, help_text="default embedding model ID", index=True) + permission = CharField(max_length=16, null=False, help_text="me|team", default="me", index=True) created_by = CharField(max_length=32, null=False, index=True) doc_num = IntegerField(default=0, index=True) token_num = IntegerField(default=0, index=True) @@ -695,20 +551,10 @@ class Knowledgebase(DataBaseModel): similarity_threshold = FloatField(default=0.2, index=True) vector_similarity_weight = FloatField(default=0.3, index=True) - parser_id = CharField( - max_length=32, - null=False, - help_text="default parser ID", - default=ParserType.NAIVE.value, - index=True) + parser_id = CharField(max_length=32, null=False, help_text="default parser ID", default=ParserType.NAIVE.value, index=True) parser_config = JSONField(null=False, default={"pages": [[1, 1000000]]}) pagerank = IntegerField(default=0, index=False) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) def __str__(self): return self.name @@ -721,119 +567,48 @@ class Document(DataBaseModel): id = CharField(max_length=32, primary_key=True) thumbnail = TextField(null=True, help_text="thumbnail base64 string") kb_id = CharField(max_length=256, null=False, index=True) - parser_id = CharField( - max_length=32, - null=False, - help_text="default parser ID", - index=True) + parser_id = CharField(max_length=32, null=False, help_text="default parser ID", index=True) parser_config = JSONField(null=False, default={"pages": [[1, 1000000]]}) - source_type = CharField( - max_length=128, - null=False, - default="local", - help_text="where dose this document come from", - index=True) - type = CharField(max_length=32, null=False, help_text="file extension", - index=True) - created_by = CharField( - max_length=32, - null=False, - help_text="who created it", - index=True) - name = CharField( - max_length=255, - null=True, - help_text="file name", - index=True) - location = CharField( - max_length=255, - null=True, - help_text="where dose it store", - index=True) + source_type = CharField(max_length=128, null=False, default="local", help_text="where dose this document come from", index=True) + type = CharField(max_length=32, null=False, help_text="file extension", index=True) + created_by = CharField(max_length=32, null=False, help_text="who created it", index=True) + name = CharField(max_length=255, null=True, help_text="file name", index=True) + location = CharField(max_length=255, null=True, help_text="where dose it store", index=True) size = IntegerField(default=0, index=True) token_num = IntegerField(default=0, index=True) chunk_num = IntegerField(default=0, index=True) progress = FloatField(default=0, index=True) - progress_msg = TextField( - null=True, - help_text="process message", - default="") + progress_msg = TextField(null=True, help_text="process message", default="") process_begin_at = DateTimeField(null=True, index=True) process_duation = FloatField(default=0) meta_fields = JSONField(null=True, default={}) - run = CharField( - max_length=1, - null=True, - help_text="start to run processing or cancel.(1: run it; 2: cancel)", - default="0", - index=True) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + run = CharField(max_length=1, null=True, help_text="start to run processing or cancel.(1: run it; 2: cancel)", default="0", index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) class Meta: db_table = "document" class File(DataBaseModel): - id = CharField( - max_length=32, - primary_key=True) - parent_id = CharField( - max_length=32, - null=False, - help_text="parent folder id", - index=True) - tenant_id = CharField( - max_length=32, - null=False, - help_text="tenant id", - index=True) - created_by = CharField( - max_length=32, - null=False, - help_text="who created it", - index=True) - name = CharField( - max_length=255, - null=False, - help_text="file name or folder name", - index=True) - location = CharField( - max_length=255, - null=True, - help_text="where dose it store", - index=True) + id = CharField(max_length=32, primary_key=True) + parent_id = CharField(max_length=32, null=False, help_text="parent folder id", index=True) + tenant_id = CharField(max_length=32, null=False, help_text="tenant id", index=True) + created_by = CharField(max_length=32, null=False, help_text="who created it", index=True) + name = CharField(max_length=255, null=False, help_text="file name or folder name", index=True) + location = CharField(max_length=255, null=True, help_text="where dose it store", index=True) size = IntegerField(default=0, index=True) type = CharField(max_length=32, null=False, help_text="file extension", index=True) - source_type = CharField( - max_length=128, - null=False, - default="", - help_text="where dose this document come from", index=True) + source_type = CharField(max_length=128, null=False, default="", help_text="where dose this document come from", index=True) class Meta: db_table = "file" class File2Document(DataBaseModel): - id = CharField( - max_length=32, - primary_key=True) - file_id = CharField( - max_length=32, - null=True, - help_text="file id", - index=True) - document_id = CharField( - max_length=32, - null=True, - help_text="document id", - index=True) + id = CharField(max_length=32, primary_key=True) + file_id = CharField(max_length=32, null=True, help_text="file id", index=True) + document_id = CharField(max_length=32, null=True, help_text="document id", index=True) class Meta: db_table = "file2document" @@ -851,10 +626,7 @@ class Task(DataBaseModel): process_duation = FloatField(default=0) progress = FloatField(default=0, index=True) - progress_msg = TextField( - null=True, - help_text="process message", - default="") + progress_msg = TextField(null=True, help_text="process message", default="") retry_count = IntegerField(default=0) digest = TextField(null=True, help_text="task digest", default="") chunk_ids = LongTextField(null=True, help_text="chunk ids", default="") @@ -863,33 +635,18 @@ class Task(DataBaseModel): class Dialog(DataBaseModel): id = CharField(max_length=32, primary_key=True) tenant_id = CharField(max_length=32, null=False, index=True) - name = CharField( - max_length=255, - null=True, - help_text="dialog application name", - index=True) + name = CharField(max_length=255, null=True, help_text="dialog application name", index=True) description = TextField(null=True, help_text="Dialog description") icon = TextField(null=True, help_text="icon base64 string") - language = CharField( - max_length=32, - null=True, - default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", - help_text="English|Chinese", - index=True) + language = CharField(max_length=32, null=True, default="Chinese" if "zh_CN" in os.getenv("LANG", "") else "English", help_text="English|Chinese", index=True) llm_id = CharField(max_length=128, null=False, help_text="default llm ID") - llm_setting = JSONField(null=False, default={"temperature": 0.1, "top_p": 0.3, "frequency_penalty": 0.7, - "presence_penalty": 0.4, "max_tokens": 512}) - prompt_type = CharField( - max_length=16, + llm_setting = JSONField(null=False, default={"temperature": 0.1, "top_p": 0.3, "frequency_penalty": 0.7, "presence_penalty": 0.4, "max_tokens": 512}) + prompt_type = CharField(max_length=16, null=False, default="simple", help_text="simple|advanced", index=True) + prompt_config = JSONField( null=False, - default="simple", - help_text="simple|advanced", - index=True) - prompt_config = JSONField(null=False, - default={"system": "", "prologue": "Hi! I'm your assistant, what can I do for you?", - "parameters": [], - "empty_response": "Sorry! No relevant content was found in the knowledge base!"}) + default={"system": "", "prologue": "Hi! I'm your assistant, what can I do for you?", "parameters": [], "empty_response": "Sorry! No relevant content was found in the knowledge base!"}, + ) similarity_threshold = FloatField(default=0.2) vector_similarity_weight = FloatField(default=0.3) @@ -898,24 +655,12 @@ class Dialog(DataBaseModel): top_k = IntegerField(default=1024) - do_refer = CharField( - max_length=1, - null=False, - default="1", - help_text="it needs to insert reference index into answer or not") + do_refer = CharField(max_length=1, null=False, default="1", help_text="it needs to insert reference index into answer or not") - rerank_id = CharField( - max_length=128, - null=False, - help_text="default rerank model ID") + rerank_id = CharField(max_length=128, null=False, help_text="default rerank model ID") kb_ids = JSONField(null=False, default=[]) - status = CharField( - max_length=1, - null=True, - help_text="is it validate(0: wasted, 1: validate)", - default="1", - index=True) + status = CharField(max_length=1, null=True, help_text="is it validate(0: wasted, 1: validate)", default="1", index=True) class Meta: db_table = "dialog" @@ -942,7 +687,7 @@ class APIToken(DataBaseModel): class Meta: db_table = "api_token" - primary_key = CompositeKey('tenant_id', 'token') + primary_key = CompositeKey("tenant_id", "token") class API4Conversation(DataBaseModel): @@ -967,17 +712,12 @@ class UserCanvas(DataBaseModel): avatar = TextField(null=True, help_text="avatar base64 string") user_id = CharField(max_length=255, null=False, help_text="user_id", index=True) title = CharField(max_length=255, null=True, help_text="Canvas title") - - permission = CharField( - max_length=16, - null=False, - help_text="me|team", - default="me", - index=True) + + permission = CharField(max_length=16, null=False, help_text="me|team", default="me", index=True) description = TextField(null=True, help_text="Canvas description") canvas_type = CharField(max_length=32, null=True, help_text="Canvas type", index=True) dsl = JSONField(null=True, default={}) - + class Meta: db_table = "user_canvas" @@ -994,6 +734,7 @@ class CanvasTemplate(DataBaseModel): class Meta: db_table = "canvas_template" + class UserCanvasVersion(DataBaseModel): id = CharField(max_length=32, primary_key=True) user_canvas_id = CharField(max_length=255, null=False, help_text="user_canvas_id", index=True) @@ -1005,152 +746,92 @@ class UserCanvasVersion(DataBaseModel): class Meta: db_table = "user_canvas_version" + def migrate_db(): with DB.transaction(): migrator = DatabaseMigrator[settings.DATABASE_TYPE.upper()].value(DB) try: - migrate( - migrator.add_column('file', 'source_type', CharField(max_length=128, null=False, default="", - help_text="where dose this document come from", - index=True)) - ) + migrate(migrator.add_column("file", "source_type", CharField(max_length=128, null=False, default="", help_text="where dose this document come from", index=True))) except Exception: pass try: - migrate( - migrator.add_column('tenant', 'rerank_id', - CharField(max_length=128, null=False, default="BAAI/bge-reranker-v2-m3", - help_text="default rerank model ID")) - - ) + migrate(migrator.add_column("tenant", "rerank_id", CharField(max_length=128, null=False, default="BAAI/bge-reranker-v2-m3", help_text="default rerank model ID"))) except Exception: pass try: - migrate( - migrator.add_column('dialog', 'rerank_id', CharField(max_length=128, null=False, default="", - help_text="default rerank model ID")) - - ) + migrate(migrator.add_column("dialog", "rerank_id", CharField(max_length=128, null=False, default="", help_text="default rerank model ID"))) except Exception: pass try: - migrate( - migrator.add_column('dialog', 'top_k', IntegerField(default=1024)) - - ) + migrate(migrator.add_column("dialog", "top_k", IntegerField(default=1024))) except Exception: pass try: - migrate( - migrator.alter_column_type('tenant_llm', 'api_key', - CharField(max_length=2048, null=True, help_text="API KEY", index=True)) - ) + migrate(migrator.alter_column_type("tenant_llm", "api_key", CharField(max_length=2048, null=True, help_text="API KEY", index=True))) except Exception: pass try: - migrate( - migrator.add_column('api_token', 'source', - CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True)) - ) + migrate(migrator.add_column("api_token", "source", CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True))) except Exception: pass try: - migrate( - migrator.add_column("tenant", "tts_id", - CharField(max_length=256, null=True, help_text="default tts model ID", index=True)) - ) + migrate(migrator.add_column("tenant", "tts_id", CharField(max_length=256, null=True, help_text="default tts model ID", index=True))) except Exception: pass try: - migrate( - migrator.add_column('api_4_conversation', 'source', - CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True)) - ) + migrate(migrator.add_column("api_4_conversation", "source", CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True))) except Exception: pass try: - migrate( - migrator.add_column('task', 'retry_count', IntegerField(default=0)) - ) + migrate(migrator.add_column("task", "retry_count", IntegerField(default=0))) except Exception: pass try: - migrate( - migrator.alter_column_type('api_token', 'dialog_id', - CharField(max_length=32, null=True, index=True)) - ) + migrate(migrator.alter_column_type("api_token", "dialog_id", CharField(max_length=32, null=True, index=True))) except Exception: pass try: - migrate( - migrator.add_column("tenant_llm", "max_tokens", IntegerField(default=8192, index=True)) - ) + migrate(migrator.add_column("tenant_llm", "max_tokens", IntegerField(default=8192, index=True))) except Exception: pass try: - migrate( - migrator.add_column("api_4_conversation", "dsl", JSONField(null=True, default={})) - ) + migrate(migrator.add_column("api_4_conversation", "dsl", JSONField(null=True, default={}))) except Exception: pass try: - migrate( - migrator.add_column("knowledgebase", "pagerank", IntegerField(default=0, index=False)) - ) + migrate(migrator.add_column("knowledgebase", "pagerank", IntegerField(default=0, index=False))) except Exception: pass try: - migrate( - migrator.add_column("api_token", "beta", CharField(max_length=255, null=True, index=True)) - ) + migrate(migrator.add_column("api_token", "beta", CharField(max_length=255, null=True, index=True))) except Exception: pass try: - migrate( - migrator.add_column("task", "digest", TextField(null=True, help_text="task digest", default="")) - ) + migrate(migrator.add_column("task", "digest", TextField(null=True, help_text="task digest", default=""))) except Exception: pass try: - migrate( - migrator.add_column("task", "chunk_ids", LongTextField(null=True, help_text="chunk ids", default="")) - ) + migrate(migrator.add_column("task", "chunk_ids", LongTextField(null=True, help_text="chunk ids", default=""))) except Exception: pass try: - migrate( - migrator.add_column("conversation", "user_id", - CharField(max_length=255, null=True, help_text="user_id", index=True)) - ) + migrate(migrator.add_column("conversation", "user_id", CharField(max_length=255, null=True, help_text="user_id", index=True))) except Exception: pass try: - migrate( - migrator.add_column("document", "meta_fields", - JSONField(null=True, default={})) - ) + migrate(migrator.add_column("document", "meta_fields", JSONField(null=True, default={}))) except Exception: pass try: - migrate( - migrator.add_column("task", "task_type", - CharField(max_length=32, null=False, default="")) - ) + migrate(migrator.add_column("task", "task_type", CharField(max_length=32, null=False, default=""))) except Exception: pass try: - migrate( - migrator.add_column("task", "priority", - IntegerField(default=0)) - ) + migrate(migrator.add_column("task", "priority", IntegerField(default=0))) except Exception: pass try: - migrate( - migrator.add_column("user_canvas", "permission", - CharField(max_length=16, null=False, help_text="me|team", default="me", index=True)) - ) + migrate(migrator.add_column("user_canvas", "permission", CharField(max_length=16, null=False, help_text="me|team", default="me", index=True))) except Exception: pass - diff --git a/api/db/services/dialog_service.py b/api/db/services/dialog_service.py index f02f9ff2d..2474475e6 100644 --- a/api/db/services/dialog_service.py +++ b/api/db/services/dialog_service.py @@ -13,26 +13,29 @@ # See the License for the specific language governing permissions and # limitations under the License. # -import logging import binascii -import time -from functools import partial +import logging import re +import time from copy import deepcopy +from functools import partial from timeit import default_timer as timer + +from langfuse import Langfuse + from agentic_reasoning import DeepResearcher +from api import settings from api.db import LLMType, ParserType, StatusEnum -from api.db.db_models import Dialog, DB +from api.db.db_models import DB, Dialog from api.db.services.common_service import CommonService from api.db.services.knowledgebase_service import KnowledgebaseService -from api.db.services.llm_service import TenantLLMService, LLMBundle -from api import settings +from api.db.services.langfuse_service import TenantLangfuseService +from api.db.services.llm_service import LLMBundle, TenantLLMService from rag.app.resume import forbidden_select_fields4resume from rag.app.tag import label_question from rag.nlp.search import index_name -from rag.prompts import kb_prompt, message_fit_in, llm_id2llm_type, keyword_extraction, full_question, chunks_format, \ - citation_prompt -from rag.utils import rmSpace, num_tokens_from_string +from rag.prompts import chunks_format, citation_prompt, full_question, kb_prompt, keyword_extraction, llm_id2llm_type, message_fit_in +from rag.utils import num_tokens_from_string, rmSpace from rag.utils.tavily_conn import Tavily @@ -41,17 +44,13 @@ class DialogService(CommonService): @classmethod @DB.connection_context() - def get_list(cls, tenant_id, - page_number, items_per_page, orderby, desc, id, name): + def get_list(cls, tenant_id, page_number, items_per_page, orderby, desc, id, name): chats = cls.model.select() if id: chats = chats.where(cls.model.id == id) if name: chats = chats.where(cls.model.name == name) - chats = chats.where( - (cls.model.tenant_id == tenant_id) - & (cls.model.status == StatusEnum.VALID.value) - ) + chats = chats.where((cls.model.tenant_id == tenant_id) & (cls.model.status == StatusEnum.VALID.value)) if desc: chats = chats.order_by(cls.model.getter_by(orderby).desc()) else: @@ -72,13 +71,12 @@ def chat_solo(dialog, messages, stream=True): tts_mdl = None if prompt_config.get("tts"): tts_mdl = LLMBundle(dialog.tenant_id, LLMType.TTS) - msg = [{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} - for m in messages if m["role"] != "system"] + msg = [{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} for m in messages if m["role"] != "system"] if stream: last_ans = "" for ans in chat_mdl.chat_streamly(prompt_config.get("system", ""), msg, dialog.llm_setting): answer = ans - delta_ans = ans[len(last_ans):] + delta_ans = ans[len(last_ans) :] if num_tokens_from_string(delta_ans) < 16: continue last_ans = answer @@ -110,6 +108,16 @@ def chat(dialog, messages, stream=True, **kwargs): check_llm_ts = timer() + langfuse_tracer = None + langfuse_keys = TenantLangfuseService.filter_by_tenant(tenant_id=dialog.tenant_id) + if langfuse_keys: + langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key, host=langfuse_keys.host) + if langfuse.auth_check(): + langfuse_tracer = langfuse + langfuse.trace = langfuse_tracer.trace(name=f"{dialog.name}-{llm_model_config['llm_name']}") + + check_langfuse_tracer_ts = timer() + kbs = KnowledgebaseService.get_by_ids(dialog.kb_ids) embedding_list = list(set([kb.embd_id for kb in kbs])) if len(embedding_list) != 1: @@ -159,8 +167,7 @@ def chat(dialog, messages, stream=True, **kwargs): if p["key"] not in kwargs and not p["optional"]: raise KeyError("Miss parameter: " + p["key"]) if p["key"] not in kwargs: - prompt_config["system"] = prompt_config["system"].replace( - "{%s}" % p["key"], " ") + prompt_config["system"] = prompt_config["system"].replace("{%s}" % p["key"], " ") if len(questions) > 1 and prompt_config.get("refine_multiturn"): questions = [full_question(dialog.tenant_id, dialog.llm_id, messages)] @@ -189,9 +196,11 @@ def chat(dialog, messages, stream=True, **kwargs): knowledges = [] if prompt_config.get("reasoning", False): - reasoner = DeepResearcher(chat_mdl, - prompt_config, - partial(retriever.retrieval, embd_mdl=embd_mdl, tenant_ids=tenant_ids, kb_ids=dialog.kb_ids, page=1, page_size=dialog.top_n, similarity_threshold=0.2, vector_similarity_weight=0.3)) + reasoner = DeepResearcher( + chat_mdl, + prompt_config, + partial(retriever.retrieval, embd_mdl=embd_mdl, tenant_ids=tenant_ids, kb_ids=dialog.kb_ids, page=1, page_size=dialog.top_n, similarity_threshold=0.2, vector_similarity_weight=0.3), + ) for think in reasoner.thinking(kbinfos, " ".join(questions)): if isinstance(think, str): @@ -200,31 +209,34 @@ def chat(dialog, messages, stream=True, **kwargs): elif stream: yield think else: - kbinfos = retriever.retrieval(" ".join(questions), embd_mdl, tenant_ids, dialog.kb_ids, 1, dialog.top_n, - dialog.similarity_threshold, - dialog.vector_similarity_weight, - doc_ids=attachments, - top=dialog.top_k, aggs=False, rerank_mdl=rerank_mdl, - rank_feature=label_question(" ".join(questions), kbs) - ) + kbinfos = retriever.retrieval( + " ".join(questions), + embd_mdl, + tenant_ids, + dialog.kb_ids, + 1, + dialog.top_n, + dialog.similarity_threshold, + dialog.vector_similarity_weight, + doc_ids=attachments, + top=dialog.top_k, + aggs=False, + rerank_mdl=rerank_mdl, + rank_feature=label_question(" ".join(questions), kbs), + ) if prompt_config.get("tavily_api_key"): tav = Tavily(prompt_config["tavily_api_key"]) tav_res = tav.retrieve_chunks(" ".join(questions)) kbinfos["chunks"].extend(tav_res["chunks"]) kbinfos["doc_aggs"].extend(tav_res["doc_aggs"]) if prompt_config.get("use_kg"): - ck = settings.kg_retrievaler.retrieval(" ".join(questions), - tenant_ids, - dialog.kb_ids, - embd_mdl, - LLMBundle(dialog.tenant_id, LLMType.CHAT)) + ck = settings.kg_retrievaler.retrieval(" ".join(questions), tenant_ids, dialog.kb_ids, embd_mdl, LLMBundle(dialog.tenant_id, LLMType.CHAT)) if ck["content_with_weight"]: kbinfos["chunks"].insert(0, ck) knowledges = kb_prompt(kbinfos, max_tokens) - logging.debug( - "{}->{}".format(" ".join(questions), "\n->".join(knowledges))) + logging.debug("{}->{}".format(" ".join(questions), "\n->".join(knowledges))) retrieval_ts = timer() if not knowledges and prompt_config.get("empty_response"): @@ -239,16 +251,13 @@ def chat(dialog, messages, stream=True, **kwargs): prompt4citation = "" if knowledges and (prompt_config.get("quote", True) and kwargs.get("quote", True)): prompt4citation = citation_prompt() - msg.extend([{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} - for m in messages if m["role"] != "system"]) + msg.extend([{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} for m in messages if m["role"] != "system"]) used_token_count, msg = message_fit_in(msg, int(max_tokens * 0.95)) assert len(msg) >= 2, f"message_fit_in has bug: {msg}" prompt = msg[0]["content"] if "max_tokens" in gen_conf: - gen_conf["max_tokens"] = min( - gen_conf["max_tokens"], - max_tokens - used_token_count) + gen_conf["max_tokens"] = min(gen_conf["max_tokens"], max_tokens - used_token_count) def decorate_answer(answer): nonlocal prompt_config, knowledges, kwargs, kbinfos, prompt, retrieval_ts, questions @@ -262,14 +271,14 @@ def chat(dialog, messages, stream=True, **kwargs): if knowledges and (prompt_config.get("quote", True) and kwargs.get("quote", True)): answer = re.sub(r"##[ij]\$\$", "", answer, flags=re.DOTALL) if not re.search(r"##[0-9]+\$\$", answer): - answer, idx = retriever.insert_citations(answer, - [ck["content_ltks"] - for ck in kbinfos["chunks"]], - [ck["vector"] - for ck in kbinfos["chunks"]], - embd_mdl, - tkweight=1 - dialog.vector_similarity_weight, - vtweight=dialog.vector_similarity_weight) + answer, idx = retriever.insert_citations( + answer, + [ck["content_ltks"] for ck in kbinfos["chunks"]], + [ck["vector"] for ck in kbinfos["chunks"]], + embd_mdl, + tkweight=1 - dialog.vector_similarity_weight, + vtweight=dialog.vector_similarity_weight, + ) else: idx = set([]) for r in re.finditer(r"##([0-9]+)\$\$", answer): @@ -278,8 +287,7 @@ def chat(dialog, messages, stream=True, **kwargs): idx.add(i) idx = set([kbinfos["chunks"][int(i)]["doc_id"] for i in idx]) - recall_docs = [ - d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx] + recall_docs = [d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx] if not recall_docs: recall_docs = kbinfos["doc_aggs"] kbinfos["doc_aggs"] = recall_docs @@ -295,7 +303,8 @@ def chat(dialog, messages, stream=True, **kwargs): total_time_cost = (finish_chat_ts - chat_start_ts) * 1000 check_llm_time_cost = (check_llm_ts - chat_start_ts) * 1000 - create_retriever_time_cost = (create_retriever_ts - check_llm_ts) * 1000 + check_langfuse_tracer_cost = (check_langfuse_tracer_ts - check_llm_ts) * 1000 + create_retriever_time_cost = (create_retriever_ts - check_langfuse_tracer_ts) * 1000 bind_embedding_time_cost = (bind_embedding_ts - create_retriever_ts) * 1000 bind_llm_time_cost = (bind_llm_ts - bind_embedding_ts) * 1000 refine_question_time_cost = (refine_question_ts - bind_llm_ts) * 1000 @@ -304,45 +313,54 @@ def chat(dialog, messages, stream=True, **kwargs): retrieval_time_cost = (retrieval_ts - generate_keyword_ts) * 1000 generate_result_time_cost = (finish_chat_ts - retrieval_ts) * 1000 - tk_num = num_tokens_from_string(think+answer) + tk_num = num_tokens_from_string(think + answer) prompt += "\n\n### Query:\n%s" % " ".join(questions) prompt = ( - f"{prompt}\n\n" - "## Time elapsed:\n" - f" - Total: {total_time_cost:.1f}ms\n" - f" - Check LLM: {check_llm_time_cost:.1f}ms\n" - f" - Create retriever: {create_retriever_time_cost:.1f}ms\n" - f" - Bind embedding: {bind_embedding_time_cost:.1f}ms\n" - f" - Bind LLM: {bind_llm_time_cost:.1f}ms\n" - f" - Tune question: {refine_question_time_cost:.1f}ms\n" - f" - Bind reranker: {bind_reranker_time_cost:.1f}ms\n" - f" - Generate keyword: {generate_keyword_time_cost:.1f}ms\n" - f" - Retrieval: {retrieval_time_cost:.1f}ms\n" - f" - Generate answer: {generate_result_time_cost:.1f}ms\n\n" - "## Token usage:\n" - f" - Generated tokens(approximately): {tk_num}\n" - f" - Token speed: {int(tk_num/(generate_result_time_cost/1000.))}/s" + f"{prompt}\n\n" + "## Time elapsed:\n" + f" - Total: {total_time_cost:.1f}ms\n" + f" - Check LLM: {check_llm_time_cost:.1f}ms\n" + f" - Check Langfuse tracer: {check_langfuse_tracer_cost:.1f}ms\n" + f" - Create retriever: {create_retriever_time_cost:.1f}ms\n" + f" - Bind embedding: {bind_embedding_time_cost:.1f}ms\n" + f" - Bind LLM: {bind_llm_time_cost:.1f}ms\n" + f" - Tune question: {refine_question_time_cost:.1f}ms\n" + f" - Bind reranker: {bind_reranker_time_cost:.1f}ms\n" + f" - Generate keyword: {generate_keyword_time_cost:.1f}ms\n" + f" - Retrieval: {retrieval_time_cost:.1f}ms\n" + f" - Generate answer: {generate_result_time_cost:.1f}ms\n\n" + "## Token usage:\n" + f" - Generated tokens(approximately): {tk_num}\n" + f" - Token speed: {int(tk_num / (generate_result_time_cost / 1000.0))}/s" ) - return {"answer": think+answer, "reference": refs, "prompt": re.sub(r"\n", " \n", prompt), "created_at": time.time()} + + langfuse_output = "\n" + re.sub(r"^.*?(### Query:.*)", r"\1", prompt, flags=re.DOTALL) + langfuse_output = {"time_elapsed:": re.sub(r"\n", " \n", langfuse_output), "created_at": time.time()} + langfuse_generation.end(output=langfuse_output) + + return {"answer": think + answer, "reference": refs, "prompt": re.sub(r"\n", " \n", prompt), "created_at": time.time()} + + if langfuse_tracer: + langfuse_generation = langfuse_tracer.trace.generation(name="chat", model=llm_model_config["llm_name"], input={"prompt": prompt, "prompt4citation": prompt4citation, "messages": msg}) if stream: last_ans = "" answer = "" - for ans in chat_mdl.chat_streamly(prompt+prompt4citation, msg[1:], gen_conf): + for ans in chat_mdl.chat_streamly(prompt + prompt4citation, msg[1:], gen_conf): if thought: ans = re.sub(r".*", "", ans, flags=re.DOTALL) answer = ans - delta_ans = ans[len(last_ans):] + delta_ans = ans[len(last_ans) :] if num_tokens_from_string(delta_ans) < 16: continue last_ans = answer - yield {"answer": thought+answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)} - delta_ans = answer[len(last_ans):] + yield {"answer": thought + answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)} + delta_ans = answer[len(last_ans) :] if delta_ans: - yield {"answer": thought+answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)} - yield decorate_answer(thought+answer) + yield {"answer": thought + answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)} + yield decorate_answer(thought + answer) else: - answer = chat_mdl.chat(prompt+prompt4citation, msg[1:], gen_conf) + answer = chat_mdl.chat(prompt + prompt4citation, msg[1:], gen_conf) user_content = msg[-1].get("content", "[content not available]") logging.debug("User: {}|Assistant: {}".format(user_content, answer)) res = decorate_answer(answer) @@ -360,27 +378,22 @@ Table of database fields are as follows: Question are as follows: {} Please write the SQL, only SQL, without any other explanations or text. -""".format( - index_name(tenant_id), - "\n".join([f"{k}: {v}" for k, v in field_map.items()]), - question - ) +""".format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question) tried_times = 0 def get_table(): nonlocal sys_prompt, user_prompt, question, tried_times - sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_prompt}], { - "temperature": 0.06}) + sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_prompt}], {"temperature": 0.06}) sql = re.sub(r".*", "", sql, flags=re.DOTALL) logging.debug(f"{question} ==> {user_prompt} get SQL: {sql}") sql = re.sub(r"[\r\n]+", " ", sql.lower()) sql = re.sub(r".*select ", "select ", sql.lower()) sql = re.sub(r" +", " ", sql) sql = re.sub(r"([;；]|```).*", "", sql) - if sql[:len("select ")] != "select ": + if sql[: len("select ")] != "select ": return None, None if not re.search(r"((sum|avg|max|min)\(|group by )", sql.lower()): - if sql[:len("select *")] != "select *": + if sql[: len("select *")] != "select *": sql = "select doc_id,docnm_kwd," + sql[6:] else: flds = [] @@ -417,11 +430,7 @@ Please write the SQL, only SQL, without any other explanations or text. {} Please correct the error and write SQL again, only SQL, without any other explanations or text. - """.format( - index_name(tenant_id), - "\n".join([f"{k}: {v}" for k, v in field_map.items()]), - question, sql, tbl["error"] - ) + """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, sql, tbl["error"]) tbl, sql = get_table() logging.debug("TRY it again: {}".format(sql)) @@ -429,24 +438,18 @@ Please write the SQL, only SQL, without any other explanations or text. if tbl.get("error") or len(tbl["rows"]) == 0: return None - docid_idx = set([ii for ii, c in enumerate( - tbl["columns"]) if c["name"] == "doc_id"]) - doc_name_idx = set([ii for ii, c in enumerate( - tbl["columns"]) if c["name"] == "docnm_kwd"]) - column_idx = [ii for ii in range( - len(tbl["columns"])) if ii not in (docid_idx | doc_name_idx)] + docid_idx = set([ii for ii, c in enumerate(tbl["columns"]) if c["name"] == "doc_id"]) + doc_name_idx = set([ii for ii, c in enumerate(tbl["columns"]) if c["name"] == "docnm_kwd"]) + column_idx = [ii for ii in range(len(tbl["columns"])) if ii not in (docid_idx | doc_name_idx)] # compose Markdown table - columns = "|" + "|".join([re.sub(r"(/.*|（[^（）]+）)", "", field_map.get(tbl["columns"][i]["name"], - tbl["columns"][i]["name"])) for i in - column_idx]) + ("|Source|" if docid_idx and docid_idx else "|") + columns = ( + "|" + "|".join([re.sub(r"(/.*|（[^（）]+）)", "", field_map.get(tbl["columns"][i]["name"], tbl["columns"][i]["name"])) for i in column_idx]) + ("|Source|" if docid_idx and docid_idx else "|") + ) - line = "|" + "|".join(["------" for _ in range(len(column_idx))]) + \ - ("|------|" if docid_idx and docid_idx else "") + line = "|" + "|".join(["------" for _ in range(len(column_idx))]) + ("|------|" if docid_idx and docid_idx else "") - rows = ["|" + - "|".join([rmSpace(str(r[i])) for i in column_idx]).replace("None", " ") + - "|" for r in tbl["rows"]] + rows = ["|" + "|".join([rmSpace(str(r[i])) for i in column_idx]).replace("None", " ") + "|" for r in tbl["rows"]] rows = [r for r in rows if re.sub(r"[ |]+", "", r)] if quota: rows = "\n".join([r + f" ##{ii}$$ |" for ii, r in enumerate(rows)]) @@ -456,11 +459,7 @@ Please write the SQL, only SQL, without any other explanations or text. if not docid_idx or not doc_name_idx: logging.warning("SQL missing field: " + sql) - return { - "answer": "\n".join([columns, line, rows]), - "reference": {"chunks": [], "doc_aggs": []}, - "prompt": sys_prompt - } + return {"answer": "\n".join([columns, line, rows]), "reference": {"chunks": [], "doc_aggs": []}, "prompt": sys_prompt} docid_idx = list(docid_idx)[0] doc_name_idx = list(doc_name_idx)[0] @@ -471,10 +470,11 @@ Please write the SQL, only SQL, without any other explanations or text. doc_aggs[r[docid_idx]]["count"] += 1 return { "answer": "\n".join([columns, line, rows]), - "reference": {"chunks": [{"doc_id": r[docid_idx], "docnm_kwd": r[doc_name_idx]} for r in tbl["rows"]], - "doc_aggs": [{"doc_id": did, "doc_name": d["doc_name"], "count": d["count"]} for did, d in - doc_aggs.items()]}, - "prompt": sys_prompt + "reference": { + "chunks": [{"doc_id": r[docid_idx], "docnm_kwd": r[doc_name_idx]} for r in tbl["rows"]], + "doc_aggs": [{"doc_id": did, "doc_name": d["doc_name"], "count": d["count"]} for did, d in doc_aggs.items()], + }, + "prompt": sys_prompt, } @@ -498,10 +498,7 @@ def ask(question, kb_ids, tenant_id): chat_mdl = LLMBundle(tenant_id, LLMType.CHAT) max_tokens = chat_mdl.max_length tenant_ids = list(set([kb.tenant_id for kb in kbs])) - kbinfos = retriever.retrieval(question, embd_mdl, tenant_ids, kb_ids, - 1, 12, 0.1, 0.3, aggs=False, - rank_feature=label_question(question, kbs) - ) + kbinfos = retriever.retrieval(question, embd_mdl, tenant_ids, kb_ids, 1, 12, 0.1, 0.3, aggs=False, rank_feature=label_question(question, kbs)) knowledges = kb_prompt(kbinfos, max_tokens) prompt = """ Role: You're a smart assistant. Your name is Miss R. @@ -523,17 +520,9 @@ def ask(question, kb_ids, tenant_id): def decorate_answer(answer): nonlocal knowledges, kbinfos, prompt - answer, idx = retriever.insert_citations(answer, - [ck["content_ltks"] - for ck in kbinfos["chunks"]], - [ck["vector"] - for ck in kbinfos["chunks"]], - embd_mdl, - tkweight=0.7, - vtweight=0.3) + answer, idx = retriever.insert_citations(answer, [ck["content_ltks"] for ck in kbinfos["chunks"]], [ck["vector"] for ck in kbinfos["chunks"]], embd_mdl, tkweight=0.7, vtweight=0.3) idx = set([kbinfos["chunks"][int(i)]["doc_id"] for i in idx]) - recall_docs = [ - d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx] + recall_docs = [d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx] if not recall_docs: recall_docs = kbinfos["doc_aggs"] kbinfos["doc_aggs"] = recall_docs diff --git a/api/db/services/langfuse_service.py b/api/db/services/langfuse_service.py new file mode 100644 index 000000000..6c94d13ce --- /dev/null +++ b/api/db/services/langfuse_service.py @@ -0,0 +1,56 @@ +# +# Copyright 2025 The InfiniFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from datetime import datetime + +import peewee + +from api.db.db_models import DB, TenantLangfuse +from api.db.services.common_service import CommonService +from api.utils import current_timestamp, datetime_format + + +class TenantLangfuseService(CommonService): + """ + All methods that modify the status should be enclosed within a DB.atomic() context to ensure atomicity + and maintain data integrity in case of errors during execution. + """ + + model = TenantLangfuse + + @classmethod + @DB.connection_context() + def filter_by_tenant(cls, tenant_id): + fields = [cls.model.host, cls.model.secret_key, cls.model.public_key] + try: + keys = cls.model.select(*fields).where(cls.model.tenant_id == tenant_id).first() + return keys + except peewee.DoesNotExist: + return None + + @classmethod + def update_by_tenant(cls, tenant_id, langfuse_keys): + fields = ["tenant_id", "host", "secret_key", "public_key"] + return cls.model.update(**langfuse_keys).fields(*fields).where(cls.model.tenant_id == tenant_id).execute() + + @classmethod + def save(cls, **kwargs): + kwargs["create_time"] = current_timestamp() + kwargs["create_date"] = datetime_format(datetime.now()) + kwargs["update_time"] = current_timestamp() + kwargs["update_date"] = datetime_format(datetime.now()) + obj = cls.model.create(**kwargs) + return obj diff --git a/api/db/services/llm_service.py b/api/db/services/llm_service.py index 274627291..15c461afc 100644 --- a/api/db/services/llm_service.py +++ b/api/db/services/llm_service.py @@ -15,10 +15,13 @@ # import logging +from langfuse import Langfuse + from api import settings from api.db import LLMType from api.db.db_models import DB, LLM, LLMFactories, TenantLLM from api.db.services.common_service import CommonService +from api.db.services.langfuse_service import TenantLangfuseService from api.db.services.user_service import TenantService from rag.llm import ChatModel, CvModel, EmbeddingModel, RerankModel, Seq2txtModel, TTSModel @@ -49,16 +52,8 @@ class TenantLLMService(CommonService): @classmethod @DB.connection_context() def get_my_llms(cls, tenant_id): - fields = [ - cls.model.llm_factory, - LLMFactories.logo, - LLMFactories.tags, - cls.model.model_type, - cls.model.llm_name, - cls.model.used_tokens - ] - objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where( - cls.model.tenant_id == tenant_id, ~cls.model.api_key.is_null()).dicts() + fields = [cls.model.llm_factory, LLMFactories.logo, LLMFactories.tags, cls.model.model_type, cls.model.llm_name, cls.model.used_tokens] + objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where(cls.model.tenant_id == tenant_id, ~cls.model.api_key.is_null()).dicts() return list(objs) @@ -114,8 +109,7 @@ class TenantLLMService(CommonService): model_config = {"llm_factory": llm[0].fid, "api_key": "", "llm_name": mdlnm, "api_base": ""} if not model_config: if mdlnm == "flag-embedding": - model_config = {"llm_factory": "Tongyi-Qianwen", "api_key": "", - "llm_name": llm_name, "api_base": ""} + model_config = {"llm_factory": "Tongyi-Qianwen", "api_key": "", "llm_name": llm_name, "api_base": ""} else: if not mdlnm: raise LookupError(f"Type of {llm_type} model is not set.") @@ -124,43 +118,32 @@ class TenantLLMService(CommonService): @classmethod @DB.connection_context() - def model_instance(cls, tenant_id, llm_type, - llm_name=None, lang="Chinese"): + def model_instance(cls, tenant_id, llm_type, llm_name=None, lang="Chinese"): model_config = TenantLLMService.get_model_config(tenant_id, llm_type, llm_name) if llm_type == LLMType.EMBEDDING.value: if model_config["llm_factory"] not in EmbeddingModel: return - return EmbeddingModel[model_config["llm_factory"]]( - model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) + return EmbeddingModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) if llm_type == LLMType.RERANK: if model_config["llm_factory"] not in RerankModel: return - return RerankModel[model_config["llm_factory"]]( - model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) + return RerankModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) if llm_type == LLMType.IMAGE2TEXT.value: if model_config["llm_factory"] not in CvModel: return - return CvModel[model_config["llm_factory"]]( - model_config["api_key"], model_config["llm_name"], lang, - base_url=model_config["api_base"] - ) + return CvModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], lang, base_url=model_config["api_base"]) if llm_type == LLMType.CHAT.value: if model_config["llm_factory"] not in ChatModel: return - return ChatModel[model_config["llm_factory"]]( - model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) + return ChatModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"]) if llm_type == LLMType.SPEECH2TEXT: if model_config["llm_factory"] not in Seq2txtModel: return - return Seq2txtModel[model_config["llm_factory"]]( - key=model_config["api_key"], model_name=model_config["llm_name"], - lang=lang, - base_url=model_config["api_base"] - ) + return Seq2txtModel[model_config["llm_factory"]](key=model_config["api_key"], model_name=model_config["llm_name"], lang=lang, base_url=model_config["api_base"]) if llm_type == LLMType.TTS: if model_config["llm_factory"] not in TTSModel: return @@ -184,7 +167,7 @@ class TenantLLMService(CommonService): LLMType.IMAGE2TEXT.value: tenant.img2txt_id, LLMType.CHAT.value: tenant.llm_id if not llm_name else llm_name, LLMType.RERANK.value: tenant.rerank_id if not llm_name else llm_name, - LLMType.TTS.value: tenant.tts_id if not llm_name else llm_name + LLMType.TTS.value: tenant.tts_id if not llm_name else llm_name, } mdlnm = llm_map.get(llm_type) @@ -195,17 +178,13 @@ class TenantLLMService(CommonService): llm_name, llm_factory = TenantLLMService.split_model_name_and_factory(mdlnm) try: - num = cls.model.update( - used_tokens=cls.model.used_tokens + used_tokens - ).where( - cls.model.tenant_id == tenant_id, - cls.model.llm_name == llm_name, - cls.model.llm_factory == llm_factory if llm_factory else True - ).execute() + num = ( + cls.model.update(used_tokens=cls.model.used_tokens + used_tokens) + .where(cls.model.tenant_id == tenant_id, cls.model.llm_name == llm_name, cls.model.llm_factory == llm_factory if llm_factory else True) + .execute() + ) except Exception: - logging.exception( - "TenantLLMService.increase_usage got exception,Failed to update used_tokens for tenant_id=%s, llm_name=%s", - tenant_id, llm_name) + logging.exception("TenantLLMService.increase_usage got exception,Failed to update used_tokens for tenant_id=%s, llm_name=%s", tenant_id, llm_name) return 0 return num @@ -213,11 +192,7 @@ class TenantLLMService(CommonService): @classmethod @DB.connection_context() def get_openai_models(cls): - objs = cls.model.select().where( - (cls.model.llm_factory == "OpenAI"), - ~(cls.model.llm_name == "text-embedding-3-small"), - ~(cls.model.llm_name == "text-embedding-3-large") - ).dicts() + objs = cls.model.select().where((cls.model.llm_factory == "OpenAI"), ~(cls.model.llm_name == "text-embedding-3-small"), ~(cls.model.llm_name == "text-embedding-3-large")).dicts() return list(objs) @@ -226,87 +201,138 @@ class LLMBundle: self.tenant_id = tenant_id self.llm_type = llm_type self.llm_name = llm_name - self.mdl = TenantLLMService.model_instance( - tenant_id, llm_type, llm_name, lang=lang) - assert self.mdl, "Can't find model for {}/{}/{}".format( - tenant_id, llm_type, llm_name) + self.mdl = TenantLLMService.model_instance(tenant_id, llm_type, llm_name, lang=lang) + assert self.mdl, "Can't find model for {}/{}/{}".format(tenant_id, llm_type, llm_name) model_config = TenantLLMService.get_model_config(tenant_id, llm_type, llm_name) self.max_length = model_config.get("max_tokens", 8192) + langfuse_keys = TenantLangfuseService.filter_by_tenant(tenant_id=tenant_id) + if langfuse_keys: + langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key, host=langfuse_keys.host) + if langfuse.auth_check(): + self.langfuse = langfuse + self.trace = self.langfuse.trace(name=f"{self.llm_type}-{self.llm_name}") + else: + self.langfuse = None + def encode(self, texts: list): + if self.langfuse: + generation = self.trace.generation(name="encode", model=self.llm_name, input={"texts": texts}) + embeddings, used_tokens = self.mdl.encode(texts) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(usage_details={"total_tokens": used_tokens}) + return embeddings, used_tokens def encode_queries(self, query: str): + if self.langfuse: + generation = self.trace.generation(name="encode_queries", model=self.llm_name, input={"query": query}) + emd, used_tokens = self.mdl.encode_queries(query) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.encode_queries can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.encode_queries can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(usage_details={"total_tokens": used_tokens}) + return emd, used_tokens def similarity(self, query: str, texts: list): + if self.langfuse: + generation = self.trace.generation(name="similarity", model=self.llm_name, input={"query": query, "texts": texts}) + sim, used_tokens = self.mdl.similarity(query, texts) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.similarity can't update token usage for {}/RERANK used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.similarity can't update token usage for {}/RERANK used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(usage_details={"total_tokens": used_tokens}) + return sim, used_tokens def describe(self, image, max_tokens=300): + if self.langfuse: + generation = self.trace.generation(name="describe", metadata={"model": self.llm_name}) + txt, used_tokens = self.mdl.describe(image, max_tokens) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens}) + return txt def describe_with_prompt(self, image, prompt): + if self.langfuse: + generation = self.trace.generation(name="describe_with_prompt", metadata={"model": self.llm_name, "prompt": prompt}) + txt, used_tokens = self.mdl.describe_with_prompt(image, prompt) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens}) + return txt def transcription(self, audio): + if self.langfuse: + generation = self.trace.generation(name="transcription", metadata={"model": self.llm_name}) + txt, used_tokens = self.mdl.transcription(audio) - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens): - logging.error( - "LLMBundle.transcription can't update token usage for {}/SEQUENCE2TXT used_tokens: {}".format(self.tenant_id, used_tokens)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens): + logging.error("LLMBundle.transcription can't update token usage for {}/SEQUENCE2TXT used_tokens: {}".format(self.tenant_id, used_tokens)) + + if self.langfuse: + generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens}) + return txt def tts(self, text): + if self.langfuse: + span = self.trace.span(name="tts", input={"text": text}) + for chunk in self.mdl.tts(text): if isinstance(chunk, int): - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, chunk, self.llm_name): - logging.error( - "LLMBundle.tts can't update token usage for {}/TTS".format(self.tenant_id)) + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, chunk, self.llm_name): + logging.error("LLMBundle.tts can't update token usage for {}/TTS".format(self.tenant_id)) return yield chunk + if self.langfuse: + span.end() + def chat(self, system, history, gen_conf): + if self.langfuse: + generation = self.trace.generation(name="chat", model=self.llm_name, input={"system": system, "history": history}) + txt, used_tokens = self.mdl.chat(system, history, gen_conf) - if isinstance(txt, int) and not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, used_tokens, self.llm_name): - logging.error( - "LLMBundle.chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, - used_tokens)) + if isinstance(txt, int) and not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens, self.llm_name): + logging.error("LLMBundle.chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens)) + + if self.langfuse: + generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens}) + return txt def chat_streamly(self, system, history, gen_conf): + if self.langfuse: + generation = self.trace.generation(name="chat_streamly", model=self.llm_name, input={"system": system, "history": history}) + + output = "" for txt in self.mdl.chat_streamly(system, history, gen_conf): if isinstance(txt, int): - if not TenantLLMService.increase_usage( - self.tenant_id, self.llm_type, txt, self.llm_name): - logging.error( - "LLMBundle.chat_streamly can't update token usage for {}/CHAT llm_name: {}, content: {}".format(self.tenant_id, self.llm_name, - txt)) + if self.langfuse: + generation.end(output={"output": output}) + + if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, txt, self.llm_name): + logging.error("LLMBundle.chat_streamly can't update token usage for {}/CHAT llm_name: {}, content: {}".format(self.tenant_id, self.llm_name, txt)) return + + output = txt yield txt diff --git a/pyproject.toml b/pyproject.toml index ed437bcbd..30c5e564f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -124,6 +124,7 @@ dependencies = [ "flasgger>=0.9.7.1,<0.10.0", "xxhash>=3.5.0,<4.0.0", "trio>=0.29.0", + "langfuse>=2.60.0", ] [project.optional-dependencies] diff --git a/uv.lock b/uv.lock index 5cd83a0d7..f44cfee51 100644 --- a/uv.lock +++ b/uv.lock @@ -1,4 +1,5 @@ version = 1 +revision = 1 requires-python = ">=3.10, <3.13" resolution-markers = [ "python_full_version >= '3.12' and sys_platform == 'darwin'", @@ -14,7 +15,7 @@ resolution-markers = [ [[package]] name = "accelerate" -version = "1.5.1" +version = "1.5.2" source = { registry = 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